National Instruments IMAQTM User Manual

IMAQ

IMAQ Vision for Visual Basic User Manual

August 2004 Edition

Part Number 371257A-01

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About This Manual

Conventions ...................................................................................................................ix

Related Documentation..................................................................................................x

Chapter 1 Introduction to IMAQ Vision

About IMAQ Vision ......................................................................................................1-1

Documentation and Examples .......................................................................................1-1

IMAQ Vision for Visual Basic Organization ................................................................1-2

cwimaq.ocx......................................................................................................1-3

CWIMAQ Control ............................................................................1-3

CWIMAQVision Control..................................................................1-3

CWIMAQViewer Control.................................................................1-3

niocr.ocx ..........................................................................................................1-4

NIOCR control..................................................................................1-4

cwmv.ocx.........................................................................................................1-4

CWMachineVision control ...............................................................1-4

ActiveX Objects ..............................................................................................1-5

Creating IMAQ Vision Applications.............................................................................1-5

Chapter 2 Getting Measurement-Ready Images

Set Up Your Imaging System ........................................................................................2-1

Calibrate Your Imaging System ....................................................................................2-2

Create an Image .............................................................................................................2-2

Acquire or Read an Image .............................................................................................2-4

Acquiring an Image .........................................................................................2-4

One-Shot Acquisition........................................................................2-4

Continuous Acquisition.....................................................................2-5

Reading a File..................................................................................................2-6

Converting an Array to an Image ....................................................................2-6

Display an Image ...........................................................................................................2-6

Attach Calibration Information......................................................................................2-7

Analyze an Image ..........................................................................................................2-7

Contents

Improve an Image.......................................................................................................... 2-9

Lookup Tables................................................................................................. 2-9

Filters .............................................................................................................. 2-9

Convolution Filter............................................................................. 2-10

Nth Order Filter ................................................................................ 2-10

Grayscale Morphology.................................................................................... 2-10

FFT.................................................................................................................. 2-11

Complex Image Operations .............................................................. 2-12

Chapter 3 Making Grayscale and Color Measurements

Define Regions of Interest............................................................................................. 3-1

Defining Regions Interactively ....................................................................... 3-1

Defining Regions Programmatically............................................................... 3-5

Defining Regions with Masks......................................................................... 3-6

Measure Grayscale Statistics......................................................................................... 3-6

Measure Color Statistics................................................................................................ 3-7

Comparing Colors ........................................................................................... 3-9

Learning Color Information ............................................................................ 3-9

Specifying the Color Information to Learn ...................................... 3-10

Using the Entire Image ..................................................................... 3-10

Choosing a Color Representation Sensitivity ................................... 3-12

Ignoring Learned Colors................................................................... 3-13

Chapter 4 Performing Particle Analysis

Create a Binary Image ................................................................................................... 4-1

Improve the Binary Image............................................................................................. 4-2

Removing Unwanted Particles........................................................................ 4-3

Separating Touching Particles ........................................................................ 4-3

Improving Particle Shapes .............................................................................. 4-4

Make Particle Measurements ........................................................................................ 4-4

Chapter 5 Performing Machine Vision Tasks

Locate Objects to Inspect .............................................................................................. 5-2

Using Edge Detection to Build a Coordinate Transformation ........................ 5-3

Using Pattern Matching to Build a Coordinate Transformation ..................... 5-5

Choosing a Method to Build the Coordinate Transformation......................... 5-7

IMAQ Vision for Visual Basic User Manual vi ni.com

Contents

Set Search Areas ............................................................................................................5-8

Defining Regions Interactively........................................................................5-8

Defining Regions Programmatically ...............................................................5-9

Find Measurement Points ..............................................................................................5-9

Finding Features Using Edge Detection..........................................................5-9

Finding Lines or Circles....................................................................5-10

Finding Edge Points Along One Search Contour .............................5-11

Finding Edge Points Along Multiple Search Contours.....................5-12

Finding Points Using Pattern Matching ..........................................................5-12

Defining and Creating Effective Template Images...........................5-13

Training the Pattern Matching Algorithm.........................................5-15

Defining a Search Area .....................................................................5-16

Setting Matching Parameters and Tolerances...................................5-17

Testing the Search Algorithm on Test Images..................................5-18

Using a Ranking Method to Verify Results ......................................5-19

Finding Points Using Color Pattern Matching ................................................5-19

Defining and Creating Effective Color Template Images ................5-20

Training the Color Pattern Matching Algorithm...............................5-21

Defining a Search Area .....................................................................5-22

Setting Matching Parameters and Tolerances...................................5-23

Testing the Search Algorithm on Test Images..................................5-25

Finding Points Using Color Location..............................................................5-25

Convert Pixel Coordinates to Real-World Coordinates.................................................5-26

Make Measurements ......................................................................................................5-26

Distance Measurements...................................................................................5-26

Analytic Geometry Measurements ..................................................................5-27

Instrument Reader Measurements ...................................................................5-28

Identify Parts Under Inspection .....................................................................................5-28

Classifying Samples ........................................................................................5-28

Reading Characters..........................................................................................5-29

Reading Barcodes............................................................................................5-29

Read 1D Barcodes.............................................................................5-29

Read Data Matrix Barcode................................................................5-30

Read PDF417 Barcode......................................................................5-31

Display Results ..............................................................................................................5-31

Contents

Chapter 6 Calibrating Images

Perspective and Nonlinear Distortion Calibration......................................................... 6-1

Defining a Calibration Template..................................................................... 6-2

Defining a Reference Coordinate System ....................................................... 6-3

Learning Calibration Information ................................................................... 6-5

Specifying Scaling Factors ............................................................... 6-6

Choosing a Region of Interest .......................................................... 6-6

Choosing a Learning Algorithm ....................................................... 6-6

Using the Learning Score ................................................................. 6-7

Learning the Error Map .................................................................... 6-8

Learning the Correction Table..........................................................6-8

Setting the Scaling Mode.................................................................. 6-8

Calibration Invalidation.................................................................... 6-9

Simple Calibration......................................................................................................... 6-9

Save Calibration Information ........................................................................................ 6-10

Attach Calibration Information ..................................................................................... 6-10

Appendix A Technical Support and Professional Services

Glossary

Index

IMAQ Vision for Visual Basic User Manual viii ni.com

About This Manual

The IMAQ Vision for Visual Basic User Manual is intended for engineers and scientists who have knowledge of Microsoft Visual Basic and need to create machine vision and image processing applications using Visual Basic objects. The manual guides you through tasks beginning with setting up the imaging system to taking measurements.

Conventions

The following conventions appear in this manual:

» The » symbol leads you through nested menu items and dialog box options

to a final action. The sequence File»Page Setup»Options directs you to pull down the File menu, select the Page Setup item, and select Options from the last dialog box.

This icon denotes a tip, which alerts you to advisory information.

This icon denotes a note, which alerts you to important information.

bold Bold text denotes items that you must select or click in the software, such

as menu items and dialog box options. Bold text also denotes parameter names.

italic Italic text denotes variables, emphasis, a cross reference, or an introduction

to a key concept. This font also denotes text that is a placeholder for a word or value that you must supply.

monospace Text in this font denotes text or characters that you should enter from the

keyboard, sections of code, programming examples, and syntax examples. This font is also used for the proper names of disk drives, paths, directories, programs, subprograms, subroutines, device names, functions, operations, variables, filenames, and extensions.

About This Manual

Note You must have the NI-IMAQ driver software installed on the target system to use the

CWIMAQ control. For information about NI-IMAQ, refer to the NI-IMAQ User Manual that came with the IMAQ device.

Chapter 1 Introduction to IMAQ Vision

cwimaq.ocx contains the following three ActiveX controls and a

collection of ActiveX objects: CWIMAQ, CWIMAQVision, and CWIMAQViewer. Refer to the ActiveX Objects section for information about the ActiveX objects.

CWIMAQ Control

Use this control to configure and perform an acquisition from the IMAQ device. The CWIMAQ control has property pages that allow you to modify various parameters to configure the acquisition and gather information about the IMAQ device. Most of the functionality available from the property pages during design time is also available through the properties of the CWIMAQ control during run-time. The control has methods that allow you to perform and control acquisitions, as well.

CWIMAQVision Control

Use this control to analyze and process images and their related data. The CWIMAQVision control provides methods for reading and writing images to and from files, analyzing images, and performing a variety of image processing algorithms on images.

CWIMAQViewer Control

Use this control to display images and provide the interface through which the user will interact with the displayed image. This includes the ability to zoom and pan images and to draw regions of interest (ROIs) on an image. The CWIMAQViewer control has property pages that allow you to configure the viewer’s appearance and behavior during design time as well as properties that you can configure during run-time. The control has methods that allow you to attach images to and detach images from the viewer for display purposes.

Note The CWIMAQViewer control is referred to as a viewer in the remainder of this

document.

Chapter 1 Introduction to IMAQ Vision

niocr.ocx

niocr.ocx provides one ActiveX control and a collection of ActiveX

objects you use in a machine vision application to perform optical character recognition (OCR).

NIOCR control

Use this control to perform OCR, which is the process by which the machine vision software reads text and/or characters in an image. OCR consists of the following two procedures:

• Training characters

• Reading characters

Training characters is the process by which you teach the machine vision software the types of characters and/or patterns you want to read in the image during the reading procedure. You can use IMAQ Vision to train any number of characters, creating a character set, which is the set of characters that you later compare with objects during the reading procedure. You store the character set you create in a character set file. Training might be a one-time process, or it might be a process you repeat several times, creating several character sets to broaden the scope of characters you want to detect in an image.

Reading characters is the process by which the machine vision application you create analyzes an image to determine if the objects match the characters you trained. The machine vision application reads characters in an image using the character set that you created when you trained characters.

cwmv.ocx

cwmv.ocx contains one ActiveX control and a collection of ActiveX

objects. Refer to the ActiveX Objects section for more information about ActiveX objects.

CWMachineVision control

Use this control to perform high-level machine vision tasks, such as measuring distances. This control is written entirely in Visual Basic using the methods on the CWIMAQVision and CWIMAQViewer controls. The source code for the CWMachineVision control is included in the product. For more information about CWMachineVision methods, refer to Chapter 5, Performing Machine Vision Tasks.

IMAQ Vision for Visual Basic User Manual 1-4 ni.com

Tip Refer to the source code of the CWMachineVision control for an example of how to

use the CWIMAQVision methods.

ActiveX Objects

Note ActiveX objects in cwimaq.ocx have a CWIMAQ prefix, objects in niocr.ocx

have an NIOCR prefix, and objects in

If you intend to develop an application in Visual C++, National Instruments

Tip

recommends that you use IMAQ Vision for LabWindows/CVI. However, if you decide to use IMAQ Vision for Visual Basic to develop applications for Visual C++, you can create objects using the respective Create methods on the CWIMAQVision control or CWMachineVision control. For example, to create a CWIMAQImage object, use the

CWIMAQVision.CreateCWIMAQImage method.

Chapter 1 Introduction to IMAQ Vision

Use the objects to group related input parameters and output parameters to certain methods, thus reducing the number of parameters that you actually need to pass to those methods.

cwmv.ocx have a CWMV prefix.

You must create an ActiveX object before you can use it. You can use the

New keyword in Visual Basic to create these objects. For example, use the

following syntax to create and store an image in a variable named

Dim image As New CWIMAQImage

image:

Creating IMAQ Vision Applications

Figures 1-1 and 1-2 illustrate the steps for creating an application with IMAQ Vision. Figure 1-1 describes the general steps for designing a Vision application. The last step in Figure 1-1 is expanded upon in Figure 1-2. You can use a combination of the items in the last step to create a IMAQ Vision application. For more information about items in either diagram, refer to the corresponding chapter listed beside the item.

Note Diagram items enclosed with dashed lines are optional steps.

Chapter 1 Introduction to IMAQ Vision

Set Up Your Imaging System

Chapter 2:

Measurement-Ready

Getting

Images

Calibrate Your Imaging System

Create an Image

Acquire or Read an Image

Display an Image

Attach Calibration Information

Analyze an Image

Improve an Image

Make Measurements or Identify Objects

in an Image Using

Grayscale or Color Measurements, and/or

Particle Analysis, and/or

Machine Vision

Chapter 6: Calibrating Images

Figure 1-1. General Steps for Designing a Vision Application

IMAQ Vision for Visual Basic User Manual 1-6 ni.com

Chapter 1 Introduction to IMAQ Vision

Making Grayscale and Color

Chapter 4:

Performing

Particle

Analysis

Measurements

Chapter 3:

Grayscale Statistics

Create a Binary Image

Improve a Binary Image

Make Particle Measurements

Define Regions of Interest

Measure

Color Statistics

Find Measurement Points

Convert Pixel Coordinates to

Real-World Coordinates

Make Measurements

Measure

Locate Objects to Inspect

Set Search Areas

Identify Parts Under Inspection

Classify Objects

Display Results

Read

Characters

Read

Symbologies

Chapter 5: Performing Machine Vision Tasks

Figure 1-2. Inspection Steps for Building a Vision Application

Getting Measurement-Ready Images

This chapter describes how to set up an imaging system, acquire and display an image, analyze the image, and prepare the image for additional processing.

Set Up Your Imaging System

Before you acquire, analyze, and process images, you must set up an imaging system. The manner in which you set up the system depends on the imaging environment and the type of analysis and processing you need to do. Your imaging system should produce images with high enough quality so that you can extract the information you need from the images.

Follow the guidelines below to set up an imaging system.

1. Determine the type of equipment you need based on the space constraints and the size of the object you need to inspect. For more information, refer to Chapter 3, System Setup and Calibration, of the IMAQ Vision Concepts Manual.

a. Make sure the camera sensor is large enough to satisfy the

minimum resolution requirement.

b. Make sure the lens has a depth of field high enough to keep all of

the objects in focus regardless of their distance from the lens. Also, make sure the lens has a focal length that meets your needs.

c. Make sure the lighting provides enough contrast between the

object under inspection and the background for you to extract the information you need from the image.

2. Position the camera so that it is parallel to the object under inspection. If the camera acquires images of the object from an angle, perspective errors occur. Even though you can compensate for these errors with software, NI recommends that you use a perpendicular inspection angle to obtain the fastest and most accurate results.

3. Select an image acquisition device that meets your needs. National Instruments offers several image acquisition devices, such as analog

Chapter 2 Getting Measurement-Ready Images

color and monochrome devices as well as digital devices. Visit

ni.com/imaq for more information about IMAQ devices.

4. Configure the driver software for the image acquisition device. If you have a National Instruments image acquisition device, configure the NI-IMAQ driver software through Measurement & Automation Explorer (MAX). Open MAX by double-clicking the Measurement & Automation Explorer icon on the desktop. For more information, refer to the NI-IMAQ User Manual and the Measurement & Automation Explorer Help for IMAQ.

Calibrate Your Imaging System

After you set up the imaging system, you may want to calibrate the system. Calibrate the imaging system to assign real-world coordinates to pixel coordinates and compensate for perspective and nonlinear errors inherent in the imaging system.

Perspective errors occur when the camera axis is not perpendicular to the object under inspection. Nonlinear distortion may occur from aberrations in the camera lens. Perspective errors and lens aberrations cause images to appear distorted. This distortion displaces information in an image, but it does not necessarily destroy the information in the image.

Use simple calibration if you want only to assign real-world coordinates to pixel coordinates. Use perspective and nonlinear distortion calibration if you need to compensate for perspective errors and nonlinear lens distortion. For detailed information about calibration, refer to Chapter 6, Calibrating

Images.

Create an Image

The CWIMAQImage object encapsulates all the information required to represent an image.

Note CWIMAQImage is referred to as an image in the remainder of this document.

An image can be one of many types, depending on the data it stores. The following image types are valid:

•8-bit

• 16-bit

• Single-precision floating point

IMAQ Vision for Visual Basic User Manual 2-2 ni.com

Chapter 2 Getting Measurement-Ready Images

• Complex

• 32-bit RGB

• 32-bit HSL

• 64-bit RGB

When you create an image, it is an 8-bit image by default. You can set the

Type property on the image object to change the image type.

When you create an image, no memory is allocated to store the image pixels. IMAQ Vision methods automatically allocate the appropriate amount of memory when the image size is modified. For example, methods that acquire or resample an image alter the image size, so they allocate the appropriate memory space for the image pixels.

Most methods belonging to the IMAQ Vision library require an input of one or more image objects. The number of images a method takes depends on the image processing function and the type of image you want to use.

IMAQ Vision methods that analyze the image but do not modify the image contents require the input of one source image. Methods that process the contents of the image require one or more source images and a destination image. Exceptions to the preceding statements are methods that take a mask image as input.

The presence of a

MaskImage parameter indicates that the processing or

analysis is dependent on the contents of the mask image. The only pixels in the source image that are processed are those whose corresponding pixels in the mask image are non-zero. If a mask image pixel is 0, the corresponding source image pixel is not processed or analyzed. The mask image must be an 8-bit image.

If you want to apply a processing or analysis method to the entire image, do not supply the optional mask image. Using the same image for both the source image and mask image also has the same effect as not using the mask image, except in this case the source image must be an 8-bit image.

Most operations between two images require that the images have the same type and size. However, arithmetic operations work between two different types of images. For example, an arithmetic operation between an 8-bit image and 16-bit image results in a 16-bit image.

Chapter 2 Getting Measurement-Ready Images

Acquire or Read an Image

After you create an image, you can acquire an image into the imaging system in one of the following three ways:

• Acquire an image with a camera through the image acquisition device.

• Load an image from a file stored on the computer.

• Convert the data stored in a 2D array to an image.

Methods that acquire images, load images from file, or convert data from a 2D array automatically allocate the memory space required to accommodate the image data.

Acquiring an Image

Use the CWIMAQ control to acquire images with a National Instruments IMAQ device. You can use IMAQ Vision for Visual Basic to perform one-shot and continuous acquisitions. You can choose the acquisition type during design time by setting the value of the Acquisition Type combo box to One-Shot or Continuous. The Acquisition Type combo box is located on the Acquisition property page of the CWIMAQ control. You can set the value at run-time by setting the

cwimaqAcquisitionOneShot or cwimaqAcquisitionContinuous.

CWIMAQ.AcquisitionType property to

One-Shot Acquisition

Use a one-shot acquisition to start an acquisition, perform the acquisition, and stop the acquisition using a single method. The number of frames acquired is equal to the number of images in the images collection. Use the

CWIMAQ.AcquireImage method to perform this operation synchronously.

Use the For information about synchronous and asynchronous acquisitions, refer to the NI-IMAQ User Manual.

If you want to acquire a single field or frame into a buffer, set the image count to 1. This operation is also referred to as a snap. Use a snap for low-speed or single capture applications. The following code illustrates a synchronous snap:

Private Sub Start_Click()

End Sub

IMAQ Vision for Visual Basic User Manual 2-4 ni.com

CWIMAQ.Start method to perform this operation asynchronously.

CWIMAQ1.AcquisitionType = cwimaqAcquisitionOneShot

CWIMAQ1.AcquireImage

Chapter 2 Getting Measurement-Ready Images

If you want to acquire multiple frames, set the image count to the number of frames you want to acquire. This operation is called a sequence. Use a sequence for applications that process multiple images. The following code illustrates an asynchronous sequence, where

numberOfImages is the

number of images that you want to process:

Private Sub Start_Click()

CWIMAQ1.AcquisitionType = cwimaqAcquisitionOneShot

CWIMAQ1.Images.RemoveAll

CWIMAQ1.Images.Add numberOfImages

CWIMAQ1.Start

End Sub

Continuous Acquisition

Use a continuous acquisition to start an acquisition and continuously acquire frames into the image buffers, and then explicitly stop the acquisition. Use the the

CWIMAQ.Stop method to stop the acquisition. If you use a single buffer

for the acquisition, this operation is called a grab. The following code illustrates a grab:

Private Sub Start_Click()

CWIMAQ1.AcquisitionType=_

cwimaqAcquisitionContinuous

CWIMAQ1.Start

End Sub

CWIMAQ.Start method to start the acquisition. Use

Private Sub Stop_Click()

CWIMAQ1.Stop

End Sub

A ring operation uses multiple buffers for the acquisition. Use a ring for high-speed applications that require processing on every image. The following code illustrates a ring, where

numberOfImages is the number of

images that you want to process:

Private Sub Start_Click()

CWIMAQ1.AcquisitionType =_

cwimaqAcquisitionContinuous

CWIMAQ1.Images.RemoveAll

CWIMAQ1.Images.Add numberOfImages

CWIMAQ1.Start

End Sub

Chapter 2 Getting Measurement-Ready Images

Private Sub Stop_Click()

CWIMAQ1.Stop

End Sub

Reading a File

Use the CWIMAQVision.ReadImage method to open and read data from a file stored on the computer into the image reference. You can read from image files stored in several standard formats, such as BMP, TIFF, JPEG, PNG, and AIPD. In all cases, the software automatically converts the pixels it reads into the type of image you pass in.

Use the image file containing additional information, such as calibration information, template information for pattern matching, or overlay information. For more information about pattern matching templates and overlays, refer to Chapter 5, Performing Machine Vision Tasks.

You also can use the to retrieve image properties—image size, pixel depth, recommended image type, and calibration units—without actually reading all the image data.

CWIMAQVision.ReadImageAndVisionInfo method to open an

Converting an Array to an Image

Use the CWIMAQImage.ArrayToImage method to convert an array to an image. You also can use the convert an image to an array.

Display an Image

Display an image using the CWIMAQViewer control. Use

CWIMAQViewer.Attach to attach the image you want the viewer

to display. When you attach an image to a viewer, the image automatically updates the viewer whenever an operation modifies the contents of the image. You can access the image attached to the viewer using the

CWIMAQViewer.Image property. Before you attach an image to the

viewer, the viewer already has an image attached by default. Therefore, the viewer has an image attached to it at all times. You can use the attached image as either a source image, destination image, or both using the

CWIMAQViewer.Image property.

CWIMAQVision.GetFileInformation method

CWIMAQImage.ImageToArray method to

You can use the CWIMAQPalette object associated with the viewer. Use the CWIMAQPalette object to programmatically apply a color palette to

IMAQ Vision for Visual Basic User Manual 2-6 ni.com

CWIMAQViewer.Palette property to access the

the viewer. You can set the CWIMAQPalette.Type property to apply predefined color palettes. For example, if you need to display a binary image—an image that contains particle regions with pixel values of 1 and a background region with pixel values of 0—set the

cwimaqPaletteBinary. For more information about color palettes, refer

to Chapter 2, Display, of the IMAQ Vision Concepts Manual.

You also can set a default palette during design time using the Menu property page. Users can change the color palette during run time by using the right-click menu on the viewer.

Attach Calibration Information

If you want to attach the calibration information of the current setup to each image you acquire, use

CWIMAQVision.SetCalibrationInformation. This method takes

in a source image that contains the calibration information and a destination image that you want to calibrate. The output image is the inspection image with the calibration information attached to it. For detailed information about calibration, refer to Chapter 6, Calibrating

Images.

Chapter 2 Getting Measurement-Ready Images

Type property to

Note Because calibration information is part of the image, it is propagated throughout

the processing and analysis of the image. Methods that modify the image size, such as geometrical transforms, void the calibration information. Use

CWIMAQVision.WriteImageAndVisionInfo to save the image and all of the

attached calibration information to a file.

Analyze an Image

When you acquire and display an image, you may want to analyze the contents of the image for the following reasons:

• To determine if the image quality is high enough for the inspection task.

• To obtain the values of parameters that you want to use in processing methods during the inspection process.

The histogram and line profile tools can help you analyze the quality of the images.

Chapter 2 Getting Measurement-Ready Images

Use CWIMAQVision.Histogram2 to analyze the overall grayscale distribution in the image. Use the histogram of the image to analyze two important criteria that define the quality of an image—saturation and contrast. If the image does not have enough light, the majority of the pixels will have low intensity values, which appear as a concentration of peaks on the left side of the histogram. If the image has too much light, the majority of the pixels will have a high intensity values, which appear as a concentration of peaks on the right side of the histogram. If the image has an appropriate amount of contrast, the histogram will have distinct regions of pixel concentrations. Use the histogram information to decide if the image quality is high enough to separate objects of interest from the background.

If the image quality meets your needs, use the histogram to determine the range of pixel values that correspond to objects in the image. You can use this range in processing methods, such as determining a threshold range during particle analysis.

If the image quality does not meet your needs, try to improve the imaging conditions to get the appropriate image quality. You may need to re-evaluate and modify each component of the imaging setup: lighting equipment and setup, lens tuning, camera operation mode, and acquisition board parameters. If you reach the best possible conditions with the setup but the image quality still does not meet your needs, try to improve the image quality using the image processing techniques described in the

Improve an Image section of this chapter.

Use

CWIMAQVision.LineProfile2 to get the pixel distribution along a

line in the image, or use

CWIMAQVision.RegionsProfile to get the

pixel distribution along a one-dimensional path in the image. By looking at the pixel distribution, you can determine if the image quality is high enough to provide you with sharp edges at object boundaries. Also, you can determine if the image is noisy, and identify the characteristics of the noise.

If the image quality meets your needs, use the pixel distribution information to determine some parameters of the inspection methods you want to use. For example, use the information from the line profile to determine the strength of the edge at the boundary of an object. You can input this information into

CWIMAQVision.FindEdges2 to find the edges

of objects along the line.

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Improve an Image

Using the information you gathered from analyzing the image, you may want to improve the quality of the image for inspection. You can improve the image with lookup tables, filters, grayscale morphology, and Fast Fourier transforms (FFT).

Lookup Tables

Apply lookup table (LUT) transformations to highlight image details in areas containing significant information at the expense of other areas. A LUT transformation converts input grayscale values in the source image into other grayscale values in the transformed image. IMAQ Vision provides four methods that directly or indirectly apply lookup tables to images:

•

Chapter 2 Getting Measurement-Ready Images

CWIMAQVision.MathLookup—Converts the pixel values of an

image by replacing them with values from a predefined lookup table. IMAQ Vision has seven predefined lookup tables based on mathematical transformations. For more information about these lookup tables, refer to Chapter 5, Image Processing, in the IMAQ Vision Concepts Manual.

CWIMAQVision.UserLookup—Converts the pixel values of an

image by replacing them with values from a user-defined lookup table.

CWIMAQVision.Equalize2—Distributes the grayscale values

evenly within a given grayscale range. Use this method to increase the contrast in images containing few grayscale values.

CWIMAQVision.Inverse—Inverts the pixel intensities of an image

to compute the negative of the image. For example, use this method before applying an automatic threshold to the image if the background pixels are brighter than the object pixels.

Filters

Filter the image when you need to improve the sharpness of transitions in the image or increase the overall signal-to-noise ratio of the image. You can choose either a lowpass or highpass filter, depending on your needs.

Lowpass filters remove insignificant details by smoothing the image, removing sharp details, and smoothing the edges between the objects and the background. You can use your own lowpass filter with

CWIMAQVision.NthOrder.

CWIMAQVision.LowPass or define

CWIMAQVision.Convolute or

Chapter 2 Getting Measurement-Ready Images

Highpass filters emphasize details, such as edges, object boundaries, or cracks. These details represent sharp transitions in intensity value. You can define your own highpass filter with or

CWIMAQVision.NthOrder, or you can use a predefined highpass

filter with

CWIMAQVision.CannyEdgeFilter. CWIMAQVision.EdgeFilter

CWIMAQVision.EdgeFilter or

allows you to find edges in an image using predefined edge detection kernels, such as the Sobel, Prewitt, and Roberts kernels.

Convolution Filter

CWIMAQVision.Convolute allows you to use a predefined set of

lowpass and highpass filters. Each filter is defined by a kernel of coefficients. Use the CWIMAQKernel object to define the filter. Use

CWIMAQKernel.LoadKernel to load a predefined kernel into the

object. If the predefined kernels do not meet your needs, use the

CWIMAQKernel.SetSize method to set the size of the kernel and the CWIMAQKernel.Element property to set the data in the kernel.

Nth Order Filter

CWIMAQVision.NthOrder allows you to define a lowpass or highpass

filter depending on the value of N that you choose. One specific Nth order filter, the median filter, removes speckle noise, which appears as small black and white dots. For more information about Nth order filters, refer to Chapter 5, Image Processing, of the IMAQ Vision Concepts Manual.

CWIMAQVision.Convolute

Grayscale Morphology

Perform grayscale morphology when you want to filter grayscale features of an image. Grayscale morphology helps you remove or enhance isolated features, such as bright pixels on a dark background. Use these transformations on a grayscale image to enhance non-distinct features before thresholding the image in preparation for particle analysis.

Grayscale morphological transformations, which include erosions and dilations, compare a pixel to those pixels that surround it. An erosion keeps the smallest pixel values. A dilation keeps the largest pixel values.

For more information about grayscale morphology transformations, refer to Chapter 5, Image Processing, of the IMAQ Vision Concepts Manual.

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FFT

Chapter 2 Getting Measurement-Ready Images

Use CWIMAQVision.GrayMorphology to perform one of the following seven transformations:

• Erosion—Reduces the brightness of pixels that are surrounded by neighbors with a lower intensity.

• Dilation—Increases the brightness of pixels surrounded by neighbors with a higher intensity. A dilation has the opposite effect of an erosion.

• Opening—Removes bright pixels isolated in dark regions and smooths boundaries.

• Closing—Removes dark pixels isolated in bright regions and smooths boundaries.

• Proper-opening—Removes bright pixels isolated in dark regions and smooths the inner contours of particles.

• Proper-closing—Removes dark pixels isolated in bright regions and smooths the inner contours of particles.

• Auto-median—Generates simpler particles that have fewer details.

Use the Fast Fourier Transform (FFT) to convert an image into its frequency domain. In an image, details and sharp edges are associated with mid to high spatial frequencies because they introduce significant gray-level variations over short distances. Gradually varying patterns are associated with low spatial frequencies.

An image can have extraneous noise, such as periodic stripes, introduced during the digitization process. In the frequency domain, the periodic pattern is reduced to a limited set of high spatial frequencies. Also, the imaging setup may produce non-uniform lighting of the field of view, which produces an image with a light drift superimposed on the information you want to analyze. In the frequency domain, the light drift appears as a limited set of low frequencies around the average intensity of the image, which is the DC component.

You can use algorithms working in the frequency domain to isolate and remove these unwanted frequencies from the image. Complete the following steps to obtain an image in which the unwanted pattern has disappeared but the overall features remain:

1. Use

CWIMAQVision.FFT to convert an image from the spatial domain

to the frequency domain. This method computes the FFT of the image and results in a complex image representing the frequency information of the image.

Chapter 2 Getting Measurement-Ready Images

2. Improve the image in the frequency domain with a lowpass or highpass frequency filter. Specify which type of filter to use with

CWIMAQVision.CxAttenuate or CWIMAQVision.CxTruncate.

Lowpass filters smooth noise, details, textures, and sharp edges in an image. Highpass filters emphasize details, textures, and sharp edges in images, but they also emphasize noise.

• Lowpass attenuation—The amount of attenuation is directly

proportional to the frequency information. At low frequencies, there is little attenuation. As the frequencies increase, the attenuation increases. This operation preserves all of the zero frequency information. Zero frequency information corresponds to the DC component of the image or the average intensity of the image in the spatial domain.

• Highpass attenuation—The amount of attenuation is inversely

proportional to the frequency information. At high frequencies, there is little attenuation. As the frequencies decrease, the attenuation increases. The zero frequency component is removed entirely.

• Lowpass truncation—Specify a frequency. The frequency

components above the ideal cutoff frequency are removed, and the frequencies below it remain unaltered.

• Highpass truncation—Specify a frequency. The frequency

components above the ideal cutoff frequency remain unaltered, and the frequencies below it are removed.

3. To transform the image back to the spatial domain, use

CWIMAQVision.InverseFFT.

Complex Image Operations

CWIMAQVision.ReplaceComplexPlane and CWIMAQVision.ExtractComplexPlane allow you to access, process,

and update independently the magnitude, phase, real, and imaginary planes of a complex image. You can also convert a complex image to an array and back with

CWIMAQImage.ArrayToImage.

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CWIMAQImage.ImageToArray and

Making Grayscale and Color Measurements

This chapter describes how to take measurements from grayscale and color images. You can make inspection decisions based on image statistics, such as the mean intensity level in a region. Based on the image statistics, you can perform many machine vision inspection tasks on grayscale or color images, such as detecting the presence or absence of components, detecting flaws in parts, and comparing a color component with a reference. Figure 3-1 illustrates the basic steps involved in making grayscale and color measurements.

Define Regions of Interest

Figure 3-1. Steps to Taking Grayscale and Color Measurements

Define Regions of Interest

An ROI is an area of an image in which you want to focus the image analysis. You can define an ROI interactively, programmatically, or with an image mask.

Defining Regions Interactively

You can interactively define an ROI in a viewer that displays an image. Use the tools from the right-click menu to interactively define and manipulate the ROIs. Table 3-1 describes each of the tools and the manner in which you use them.

Measure

Grayscale Statistics

Measure

Color Statistics

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WARNING REGARDING USE OF NATIONAL INSTRUMENTS PRODUCTS

Contents

About This Manual

Conventions

Related Documentation

IMAQ Vision

NI Vision Assistant

NI Vision Builder for Automated Inspection

Other Documentation

About IMAQ Vision

Documentation and Examples

IMAQ Vision for Visual Basic Organization

cwimaq.ocx

CWIMAQ Control

CWIMAQVision Control

CWIMAQViewer Control

niocr.ocx

NIOCR control

cwmv.ocx

CWMachineVision control

ActiveX Objects

Creating IMAQ Vision Applications

Figure 1-1. General Steps for Designing a Vision Application

Figure 1-2. Inspection Steps for Building a Vision Application

Set Up Your Imaging System

Calibrate Your Imaging System

Create an Image

Acquire or Read an Image

Acquiring an Image

One-Shot Acquisition

Continuous Acquisition

Reading a File

Converting an Array to an Image

Display an Image

Attach Calibration Information

Analyze an Image

Improve an Image

Lookup Tables

Filters

Convolution Filter

Nth Order Filter

Grayscale Morphology

Complex Image Operations

Define Regions of Interest

Figure 3-1. Steps to Taking Grayscale and Color Measurements

Defining Regions Interactively